Absolute Versus Relative Changes in Cardiac Troponins in the Diagnosis of Myocardial Infarction: A Systematic Review and Meta-Analysis

Ischemic heart disease (IHD) is one of the leading causes of death globally. Rapid diagnosis of myocardial infarction (MI) will enable earlier initiation of the treatment and improve patient outcomes. Practice guidelines for non-ST-elevation acute coronary syndromes by the American College of Cardiology (ACC)/American Heart Association (AHA) had listed the diagnostic performance of absolute versus relative changes in evidence gaps. We aimed to address this evidence gap by examining the diagnostic accuracy of absolute versus relative changes in cardiac troponins at various time intervals in diagnosing MI. Grey literature, conference abstracts, animal studies, and reports published before 2009 and in languages other than English were excluded. We included reports that investigated absolute or relative changes in highly sensitive cardiac troponin T (hs-cTnT) or sensitive/highly sensitive cardiac troponin I (s/hs-cTnI) assays after specific time intervals (1, 2, or 3 h) in patients presenting with symptoms suggestive of the acute coronary syndrome. After screening, we arranged the reports in 12 separate groups based on the variables for which the data was reported. Quality assessment of the diagnostic accuracy studies-2 (QUADAS-2) was used to assess the risk of bias in the included studies. The weighted summary area under the curve (AUC) was calculated for each pool. We then performed two-sided (or two-tailed) tests to compare independent receiver operating characteristic (ROC) curves. MedCalc version 20.106 (MedCalc Software Ltd., Ostend, Belgium) was used for all statistical analysis. We included eight reports with 23,450 patients in the meta-analysis. Weighted summary estimates and their respective 95% confidence intervals (CI) under random-effects model for ROC-AUC are as follows: absolute hs-cTnI at 1 h - 0.94 (95% CI: 0.922 to 0.959, p < 0.001); absolute hs-cTnT at 1 h - 0.921 (95% CI: 0.902 to 0.941, p < 0.001); absolute s/hs-cTnI at 2 h - 0.953 (95% CI: 0.926 to 0.980, p < 0.001); absolute hs-cTnT at 2 h 0.951 (95% CI: 0.940 to 0.962, p < 0.001); relative hs-cTnT at 2 h - 0.818 (95% CI: 0.733 to 0.903, p < 0.001); relative s/hs-cTnI at 2 h - 0.762 (95% CI: 0.726 to 0.798, p < 0.001); absolute hs-cTnI at 3 h - 0.967 (95% CI: 0.95 to 0.984, p < 0.001); absolute hs-cTnT at 3 h - 0.959 (95% CI: 0.950 to 0.968, p < 0.001); and relative hs-cTnT at 3 h - 0.926 (95% CI: 0.907 to 0.945, p < 0.001). P-values of comparison of absolute and relative changes are as follows: hs-cTnT at 1 h: <0.0001; hs-cTnI at 1 h: <0.0001; hs-cTnT at 2 h: 0.0024; s/hs-cTnI at 2 h: <0.0001; hs-cTnT at 3 h: 0.0022; and hs-cTnI at 3 h: 0.0005. Our analysis found absolute changes to be superior to relative changes in both hs-cTnT and s/hs-cTnI at 1, 2, and 3 h in the diagnosis of MI. There was no statistically significant difference in comparing s/hs-cTnI vs. hs-cTnT using absolute or relative changes at any time interval. Our findings suggest that future research investigating a potential 0 h/30 min algorithm should use absolute Δ over relative Δ. A suboptimal number of reports in the groups limited our ability to establish the robustness of the results. We did not receive any funding for this review.


Introduction And Background
Ischemic heart disease (IHD) is one of the leading causes of death globally, with 16% of the world's total deaths (8.9 million deaths) attributed to it in 2019. From 2000 to 2019, the number of deaths due to IHD increased by more than two million, which was the most significant increase in deaths during this period for any disease [1].
Rapid diagnosis of myocardial infarction (MI) will enable earlier initiation of the treatment and improve patient outcomes. Diagnostic criteria of acute MI are the detection of an increase and/or decrease of cardiac 1 2 1 1 1 troponin (cTn) values with at least one value above the 99th percentile of the upper reference limit (URL) and at least one of the following: symptoms of myocardial ischemia, new ischemic changes on electrocardiogram (ECG), development of pathological Q waves on ECG, imaging evidence of recent loss of viable myocardium or new abnormality in wall motion in a pattern consistent with an ischemic etiology, and intracoronary thrombus identified on angiography or autopsy. The levels of cTn serve as quantitative markers of myocardial injury. The increase and/or decrease of cTn values represent an acute injury of the myocardium [2]. According to the current universal definition of MI, cardiac troponins are integral to diagnosing acute MI.
The use of cardiac troponin is the most rapidly evolving area in the early diagnosis of the non-ST-elevation acute coronary syndrome [3]. The advent of cardiac troponin T and I assays have seen them outperforming cardiac biomarkers like creatine kinase-myocardial band isoenzyme (CK-MB) and myoglobin, which offered little additional diagnostic value [4]. Technological advancements in sensitive-cardiac troponin (s-cTn) and, later, highly sensitive cardiac troponin assays (hs-cTn assays) had higher sensitivity and diagnostic accuracy. They enabled a more rapid diagnosis of MI than standard cTn assays. The hs-cTn assays have also reduced the diagnosis of unstable angina (UA) and allowed for better differentiation of non-ST-elevation myocardial infarction (NSTEMI) from unstable angina and other cardiac diseases [5]. Serial measurements of hs-cTn assays further increase the diagnostic accuracy. Practice guidelines for the management of patients with non-ST-elevation acute coronary syndromes by the American College of Cardiology (ACC)/American Heart Association (AHA) had listed the diagnostic performance of absolute versus relative changes on serial measurements in evidence gaps [3]. Many studies have investigated absolute and relative changes in cardiac troponins in the diagnosis of MI [6]. This area is relatively less explored in terms of systematic reviews and meta-analyses.
We aimed to address an evidence gap in practice guidelines for a leading global cause of death by examining the diagnostic performance of absolute versus relative changes in cardiac troponins at various time intervals in diagnosing MI.

Review Methods
We have followed the guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 statement to conduct and report this systematic review and meta-analysis [7].

Databases and Search Strategies
We used PubMed, PubMed Central (PMC), MEDLINE, and Google Scholar for a comprehensive search to identify the studies. We last searched the above databases in April 2022. Search strategies for various databases are presented in Table 1.

Databases Search strategy
PubMed/PMC/MEDLINE (absolute OR relative OR change* OR delta) AND ("troponin I" OR "Troponin I"[Mesh] OR "troponin T" OR "Troponin T"[Mesh] OR cTnT OR cTnI OR hs-cTnT OR hs-cTnI OR high-sensitivity* OR troponin*) AND (AUC OR "diagnostic accuracy" OR "early diagnos*" OR "Early Diagnosis"[Mesh] OR diagnos* OR "Diagnosis"[Mesh]) AND ("myocardial infarction" OR "Myocardial Infarction"[Mesh] OR MI) Google Scholar (absolute relative change delta) AND (troponin) AND (diagnostic accuracy early diagnosis) AND (myocardial infarction) We explored the reference lists of the retrieved studies for more relevant studies.

Exclusion and Inclusion Criteria
We screened studies by titles and abstracts based on the following exclusion and inclusion criteria. Animal studies and studies published before 2009 and in languages other than English were filtered out. We excluded grey literature, conference abstracts, and studies investigating cTn changes after cardiac reperfusion. We included studies investigating absolute or relative changes in hs-cTnT or s/hs-cTnI after specific time intervals (1, 2, or 3 h) in patients presenting with symptoms suggestive of acute coronary syndrome. Studies were screened by consensus whenever necessary.
Absolute change and relative change are calculated using the following equations:

Quality Assessment
We used the Quality Assessment of the Diagnostic Accuracy Studies-2 (QUADAS-2) tool to assess the included studies' quality [8]. A consensus strategy was adopted whenever necessary.

Data Extraction
We initially collected data for our study characteristics table from the included studies. We encountered multiple reports investigating different strategies/hs-cTnI assays by various manufacturers in patients enrolled in the Advantageous Predictors of Acute Coronary Syndromes Evaluation (APACE) study during the same enrolment period. We pooled comparable data from multiple reports from this study only if the patient enrolment period differed. We only pooled data from standalone absolute or relative changes for the s/hs-cTn. We collected the data for the area under the curve (AUC) values and their respective 95% confidence intervals (CI) for all the above variables. Standard error values were then calculated from 95% CI using the following formula: (Upper limit of 95% CI-the lower limit of 95% CI)/3.92 [9].
We did not collect data for metrics like sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). These metrics are reported for a specific cut-off value. Studies have reported data for sensitivity, specificity, PPV, and NPV at different cut-off values of absolute and relative changes. Pooling AUC for receiver operating characteristic (ROC) curves is inherently more reliable in the above context.

Statistical Analysis
We pooled reports separately based on a time interval (1, 2, or 3 h), type of change (absolute or relative), and type of cTn (hs-cTnT or s/hs-cTnI). The weighted summary AUC was then calculated for each pool. Twosided (or two-tailed) tests were then performed using the weighted summary AUC and standard error (SE) calculated under the random-effects model to test the statistical significance of the difference between the AUC curves of absolute vs. relative changes and hs-cTnT vs. s/hs-cTnI assays. The weighted summary AUC values under the random-effects model of absolute and relative, hs-cTnT and s/hs-cTnT, at 1, 2, and 3 h time intervals were then used to make a visual presentation of AUC trends over time using Microsoft Excel version 2204 (Microsoft Corporation, Redmond, Washington). In cases where there was only one report in a group, we used the AUC value and 95% CI from this single report to test for statistical significance of the difference between the AUC curves and plot the graph depicting AUC trends over time.
We assessed heterogeneity using Cochran's Q and I 2 statistics. MedCalc version 20.106 (MedCalc Software Ltd., Ostend, Belgium) was used for all statistical analysis.

Results
We sought 45 reports for retrieval, and only eight reports were included in the meta-analysis. Studies reporting absolute or relative changes in combination with variables like baseline cTn > 99th percentile using AND or OR conditions made them incomparable with our data of interest. Some studies did not report AUC values and their respective 95% CI for absolute or relative changes. Many reports investigating different assays and strategies from a single, large, ongoing, international, multicenter study (APACE) were excluded because of overlap in their patient enrolment periods. Reports from this study were grouped only if the enrolment period of the studies did not overlap. The PRISMA flow diagram for identifying studies via databases is presented in Figure 1.

FIGURE 1: PRISMA (Preferred Reporting Items for Systematic reviews and Meta-Analysis) flow diagram
The total number of patients in the eight reports included in the meta-analysis is 23,450. Two out of eight studies included in the meta-analysis are retrospective studies, and all others are prospective studies. Five studies excluded patients with ST-segment elevation myocardial infarction (STEMI). The mean/median age and the percentage of male gender in the total study sample in individual studies ranged from 60 to 67 and 52.7%-78%, respectively, among the reports reporting these data. The mean/median time from symptom onset to the first blood draw in the total study sample in individual studies ranged from 2.75 to 6.3 h, among the reports reporting these data. The characteristics of each included report are presented in Table 2.  Reports were placed in 12 separate groups based on the variables for which the data was reported, as shown in Table 3.

Meta-analysis
Meta-analysis was performed for nine of the 12 groups, with at least two reports, as shown in Table 3. Metaanalyses and forest plots of those nine groups are presented in Tables 4-12

TABLE 14: AUC values in various groups
The AUC values in Table 14 and their respective standard errors under the random-effects model in Tables  4-12 and underlying studies (in cases where there is only one report in the group) are used to compare independent ROC curves as shown in Tables 15, 16.

Comparison P-value
Absolute vs relative changes in hs-cTnT at 1 h <0.0001 Absolute vs relative changes in hs-cTnI at 1 h <0.0001 Absolute vs relative changes in hs-cTnT at 2 h 0.0024 Absolute vs relative changes in s/hs-cTnI at 2 h <0.0001 Absolute vs relative changes in hs-cTnT at 3 h 0.0022 Absolute vs relative changes in hs-cTnI at 3 h 0.0005  The AUC values in Table 14 are used to plot the AUC trends over a time graph as shown in Figure 9.

Discussion
Cardiac troponin changes (Δ) on a serial assessment are integral to the rapid "rule-in" and "rule-out" algorithms like the 0 h/1 h algorithm (blood drawn at 0 h and 1 h) or the 0 h/2 h algorithm (blood drawn at 0 h and 2 h) recommended by the current European Society of Cardiology (ESC) guidelines [18]. High sensitivitycardiac troponin assays (hs-cTn) have allowed for a considerable shortening of the interval to second cardiac troponin assessment to 1 h/2 h. This meta-analysis validates and reinforces the use of absolute changes over relative changes in the algorithms recommended by current ESC guidelines. We observed a statistically significant difference for all comparisons of AUC values of absolute versus relative Δ we performed. There was no statistically significant difference in comparing s/hs-cTnI vs. hs-cTnT using absolute or relative changes at any time interval.
Our findings show a trend of a more dramatic increase in AUC values over time for relative changes than absolute changes as shown in Figure 7. The difference between AUC values between absolute versus relative changes is widest at 1 h and gets closer at 3 h time interval. So, our findings suggest that future research investigating a potential 0 h/30min algorithm should use absolute changes and agree with studies like Yokoyama et al. [19].
When hs-cTn assays are unavailable and conventional cTn assays are used instead, which might necessitate a delayed second troponin assessment, the superiority of absolute over relative Δ needs to be established at that delayed time interval. The above question is out of the scope of this meta-analysis since we examined the performance of s/hs-cTnI and hs-cTnT assays.

Limitations
Lack of access to databases like Embase, Web of Science, Cochrane, and Scopus is potentially a significant limitation of this report. Out of 12 groups shown in Table 3, three groups had only one report, and five had only two reports. All three groups with only one report in them were regarding relative changes. We used the data from only one report in those groups to test for statistical significance difference between AUC values of absolute versus relative changes.
Furthermore, in groups with only two reports, we were unable to establish the robustness of the analysis because we were unable to perform sensitivity analysis. The above reason also limited our ability to explore the possible causes of heterogeneity. We pooled data from sensitive-cTnI and highly sensitive-cTnI assays together, a potential cause of heterogeneity in those groups.

Conclusions
Our analysis found absolute changes to be superior to relative changes in both hs-cTnT and s/hs-cTnI at 1, 2, and 3 h in the diagnosis of MI. We observed a statistically significant difference in all comparisons of AUC values of absolute versus relative Δ we performed. There was no statistically significant difference in comparing s/hs-cTnI vs. hs-cTnT using absolute or relative changes at any time interval. Our findings suggest that future research investigating a potential 0 h/30 min algorithm should use absolute Δ over relative Δ.

Conflicts of interest:
In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work.